2027 Summer Intern - Machine Learning Engineer, AV/AI Platform

General Motors; Sunnyvale (CA); Presencial; USD 90.000 - 132.000; Jornada completa

Descripción de la vacante

General MotorsAV/AI Platform team is building a state-of-the-art AI training platform to accelerate autonomous driving development. This internship focuses on data processing, model training and inference workflows, and improving testing infrastructure to boost reliability and reduce latency.

You will work with engineers to develop scalable infrastructure, collect requirements for feature roadmaps, and implement code with C++ and Python while exploring distributed and accelerator-enabled ML

Formación

• Pursuing a Bachelor's or Master's degree in CS, AI, ML, robotics, or related STEM field.
• Graduating between Dec 2027 and Aug 2029 with at least one semester remaining.
• Available for full-time, 12 weeks in Summer 2027.
• Strong foundation in algorithms and data structures; proficient in C++ or Python.
• Experience in AI/ML coursework or projects.
• Strong communication and collaboration skills.

Responsabilidades

• Develop scalable infrastructure and tools to support model training and deployment to edge devices, egression, and rules-based models, operations, and inference.
• Collect requirements with managers to create feature roadmap.
• Code deliverables with the engineering team.
• Adapt ML methods to exploit parallel environments (clusters, multicore, GPU).
• Perform responsibilities varying by team.

Conocimientos

C++

Python

Algorithms

Data Structures

ML basics

Team Collaboration

Communication

Educación

Bachelor's or Master's in CS/AI/Engineering

Herramientas

PyTorch

CUDA

Kubernetes

Descripción del empleo

Job Description

About the Team:

GM's AV/AI Platform organization builds the software foundation and engineering tools that power safe, reliable, and scalable autonomous driving and advanced driver-assistance systems. We are building a state-of-the-art AI training platform in close collaboration with model teams to deliver Autonomous car milestones, maximizing model flop utilization and iteration speed, and enhancing inference systems. We are augmenting training, data processing, evaluation and the deployment loop with a data flywheel to validate performance and continuously improve Autonomous driving and Active Safety. W e accelerate compute performance through architectural changes and low-level optimizations, informed by advanced HIL platforms, AI tooling and workflows and instrumentation built in-house. We streamline compiler/build and modelbench performance; enhance data processing, preprocessing, and batch inference; and improve monitoring and availability to increase velocity and quality.

About the Role:

As an intern, you will help develop and optimize our AI training platform by improving data processing pipelines, accelerating model training and inference workflows, and/ or enhancing testing infrastructure. You will support tool development, instrumentation, and system monitoring to boost reliability, reduce latency, and increase iteration speed for advancing autonomous driving performance.

What You'll Do:

• Develop scalable infrastructure and tools to support model training, model deployment to the edge devices, egression, and rules-based models, operations, and inference.
• Suggest, collect and synthesize requirements and work with your managers or tech leads to create feature roadmap
• Code deliverables in tandem with the engineering team.
• Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
• Perform specific responsibilities which vary by team.

Required Qualifications:

• Currently enrolled in a full-time, degree-seeking program and in the process of obtaining a Bachelor's or Master's degree in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.
• Must be graduating between December 2027 and August 2029 and have at least one additional quarter/semester of school remaining following the completion of the internship.
• Availability to work full-time, 40 hours per week, during the 12 week summer internship period between May 24th - August 13th or June 14th - September 3rd 2027
• Strong foundation in algorithms and data structures, with proficiency in C++, Python, or another object-oriented programming language.
• Demonstrated coursework, project, research, or applied experience in artificial intelligence or machine learning
• Experience with algorithms, software development, or systems engineering fundamentals
• Strong written and verbal communication skills and the ability to collaborate across teams.

Preferred Qualifications

• Demonstrated software engineering experience through an internship, work experience, coding competition, student engineering team or competition (e.g., SAE student competitions, EcoCAR, Formula SAE, or Baja SAE), research, coursework, or personal project. Relevant experience may include vehicle systems, autonomy, robotics, embedded software, controls, simulation, sensor data, or ML; exposure to AI-assisted development tools, agentic workflows, or LLM-powered tools is a plus.
• Familiarity with AI -assisted engineering tools (e.g., for code generation, model analysis, or experiment planning) to enhance productivity and understanding of ML systems.
• Demonstrated creativity and quick problem-solving capabilities.
• Research and/or work experience in a relevant field, such as machine learning, deep learning, reinforcement learning, NLP, recommendation systems, pattern recognition, signal processing, data mining artificial intelligence, or computer vision
• Experience programming in C++, Python, or another object-oriented language
• Exposure to distributed systems and ML infrastructure, such as Spark, Ray, Kubernetes, Slurm, PyTorch, TensorRT, ONNX, Kubeflow, or similar technologies, and/or accelerator programming with CUDA, OpenCL, Triton, or related tools.
• Experience with distributed systems (e.g., Spark, Ray, Kubernetes, Slurm)
• Experience in CUDA, OpenCL, Triton or other accelerator programming language.
• Passion for self-driving technology and its potential impact on the world

Compensation:

The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

The salary range for this role is $8,100 - 11,800 per month. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

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